跳至主要内容
临床试验/NCT05865184
NCT05865184招募中不适用

Feasibility of Home-based, Ambient Passive Sensor Technology to Provide Early Warning of Health Decompensation by Detecting Deviations in Activities of Daily Living (ADLs) of Elderly Subjects With Diagnosed Chronic Disease

Sensorum Health Inc.1 个研究点 分布在 1 个国家目标入组 100 人开始时间: 2022年9月28日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
100
试验地点
1
主要终点
Precision of AI in passive sensor system

研究概览

简要总结

Sensorum Health (Sensorum) is conducting a pilot study to determine if Sensorum's proprietary passive sensor network can be used to identify signals of early health decompensation in subjects prior to a hospitalization for chronic disease exacerbation or other ambulatory care sensitive conditions. Successful early detection would provide a window of opportunity to intervene outside of the acute setting in future interventional studies.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
65 Years 至 —(Older Adult)
性别
All
接受健康志愿者

入选标准

  • Aged 65 years or older
  • Able to consent
  • Documented history of diagnosis of chronic obstructive pulmonary disease (COPD) and/or congestive heart failure (CHF)
  • Currently admitted to JSUMC for observation or as an inpatient with any diagnosis ≥1 prior hospital utilization events with any diagnosis (inpatient admissions, facility observation stays, or ED visits) in the past 12 months

排除标准

  • Significant cardiac valvular disease
  • End-Stage Renal Disease (ESRD)
  • End-Stage CHF
  • End-Stage COPD

结局指标

主要结局

Precision of AI in passive sensor system

时间窗: 90 days

Evaluation of AI ability to precisely predict hospital utilization event

Recall of AI in passive sensor system

时间窗: 90 days

Evaluation of AI ability to prospectively detect hospital utilization event

次要结局

  • Recall of sensor data review by trained nurses(90 days)
  • Precision of sensor data review by trained nurses(90 days)

研究者

申办方类型
Industry
责任方
Sponsor

研究点 (1)

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